System and method for determining the desirability of video programming events using keyword matching

ABSTRACT

The desirability of programming events may be determined using metadata for programming events that includes goodness of fit scores associated with categories of a classification hierarchy one or more of descriptive data and keyword data. The programming events are ranked in accordance with the viewing preferences of viewers as expressed in one or more viewer profiles. The viewer profiles may each include preference scores associated with categories of the classification hierarchy and may also include one or more keywords. Ranking is performed through category matching and keyword matching using the contents of the metadata and the viewer profiles. The viewer profile keywords may be qualified keywords that are associated with specific categories of the classification hierarchy. The ranking may be performed such that qualified keyword matches generally rank higher than keyword matches, and keyword matches generally rank higher than category matches. In alternative embodiments, scores may be calculated such that the ranges of scores for qualified keyword matches, keyword matches and category matches are overlapping but are generally ordered as previously described. Related embodiments may pertain to systems that implement such methods. Program rankings may be used to generate an alert schedule for providing alerts to viewers regarding programming events.

CONTINUING DATA

This application claims priority under 35 USC § 119(e) from U.S.Provisional Application Ser. No. 60/249,179, filed 16 Nov. 2000, theentirety of which is incorporated herein by reference. This applicationis a continuation of U.S. Ser. No. 09/992,686 filed 16 Nov. 2001, whichis a continuation in part of U.S. application Ser. Nos. 09/793,294,09/793,322, 09/793,357, and 09/793,479, each filed 26 Feb. 2001, theentirety of each of which is incorporated herein by reference.

This application is related to the following applications: System andMethod for Generating Metadata for Programming Events, Ser. No.09/991,807, filed concurrently herewith; Interactive System and Methodfor Generating Metadata for Programming Events, Ser. No. 09/991,741,filed concurrently herewith; System and Method for Providing Timing Datafor Programming Events, Ser. No. 09/992,882, filed concurrentlyherewith; System and Method for Using Programming Event Timing Data in aRecording Device, Ser. No. 09/991,814, filed concurrently herewith;System and Method for Creating and Editing a Viewer Profile Used inDetermining the Desirability of Video Programming Events, Ser. No.09/992,414, filed concurrently herewith; and System and Methods forDetermining the Desirability of and Recording Video Programming Events,Serial No. PCT/US02/36328, filed concurrently herewith, each of which isincorporated herein by reference.

BACKGROUND

1. Field of the Invention

Embodiments of the invention relate to technologies that enable theidentification of programming events of interest to a viewer.

2. Related Technology

Television viewers are presently able to access hundreds of channelsproviding a multitude of programs, only a small fraction of which willbe of interest to a given viewer. To assist the viewer in determiningprograms of interest, current commercially available reception devicessuch as televisions, analog cable receivers, and digital cable andsatellite receivers typically provide a program guide function thatallows the viewer to access a grid showing programs that will beavailable on various channels in upcoming time slots. Brief descriptionsof programs may also be accessible. Such receivers may also allow theuser to search for programs in basic categories such as news, sports,movies, etc.

Current commercially available television recording technology alsoprovides similar tools. The present generation of digital videorecording machines, which typically store video on a bulk storage devicesuch as a hard disk drive, allow users to select programs for recordingusing an on screen program guide that provides keyword searching ofprogram titles, a program time grid, and basic program categorization.

Although these devices provide tools that improve over devices ofearlier generations, most conventional tools still require viewers toexamine all upcoming programs to identify programs of interest. Thus,developers of the next generation of devices are focused on providingintelligence in receiving and recording devices for identifying programsof interest on behalf of the user. A number of U.S. patents describedifferent approaches to this problem.

U.S. Pat. No. 5,223,924 describes a device that downloads programdescriptions. The program descriptions are viewed individually by auser, who indicates whether he is interested in each program. Based onthe user's input, the device builds a database of keywords associatedwith the user's positive and negative preferences. This database is thenused to identify upcoming programs that may be of interest to the user.

U.S. Pat. No. 5,410,344 describes a device that stores a viewerpreference file that reflects the viewer's positive and negativepreferences concerning various program attributes. The device uses thepreference file to analyze content codes that describe attributes ofavailable programs, and presents a program to the user based on theanalysis. Programs are ranked using a neural network thresholdingmethod.

U.S. Pat. No. 5,434,678 and its related patents describe a videoretrieval system in which individual portions of scenes within a videoare rated in accordance with a rating system and a version of the videois presented by selecting the segments that are acceptable based on auser's content preferences. Similar technology is described in U.S. Pat.No. 5,717,814 and its related patents.

U.S. Pat. No. 5,444,999 describes a device that tracks the viewinghabits of a user and builds a weekly viewing trend. The device notifiesthe viewer when the television is tuned to different channel in conflictwith the viewing trend.

U.S. Pat. No. 5,534,911 describes a system in which a viewer builds apersonal profile that is then used to analyze data describing availableprograms. Programs are selected based on the analysis and are madeavailable on a personalized virtual channel. The viewer is also enabledto select from among programs that are ranked in accordance with theprofile. The specific manner in which program analysis is performed isnot described.

U.S. Pat. No. 5,585,865 describes a system that searches for a genrecode in broadcast signals in accordance with a specified program genre.If more than one signal contains the desired genre code, the systemdisplays the channel with the greatest display history.

U.S. Pat. No. 5,619,247 describes a video recording device that selectsprograms for storage based on predefined user preferences, and allows auser to view the stored programs on a pay-per-view basis.

U.S. Pat. No. 5,767,893 describes a system that uses content basedfiltering for identifying video programs to be stored. The specificmanner in which content is filtered is not described.

U.S. Pat. No. 5,878,222 describes a system that monitors channel datadescribing contents of available channels and arbitrates access todisplay or storage resources based on a user profile.

U.S. Pat. No. 5,945,988 describes a system that monitors the programsviewed by a current viewer and determines the identity of the currentviewer using stored viewer profiles. The system may then use the viewerprofile to analyze metadata describing upcoming programs to identifyprograms for viewing or recording. The specific manner in which themetadata analysis is performed is not described.

U.S. Pat. No. 6,088,722 describes a system in which a user profile iscompared to program content profiles to generate an agreement matrix foreach program. The agreement matrixes are used to select a program forpresentation to the viewer. Agreement matrixes may also be generated ata server end using profiles for multiple viewers to select programs tobe made available from the server.

SUMMARY OF THE DISCLOSURE

One shortcoming of the conventional technology as described above isthat programs must be evaluated on a whole-program basis. However, manyprograms address diverse subjects, some of which will be of interest toa particular viewer and some of which will not. Embodiments of theinvention address this problem through devices and processes forgenerating metadata for individual program segments, thus allowingprogram segments to be treated as individual programming events that canbe individually evaluated by the user or by user equipment. Relatedembodiments of the invention are applicable to programs such as newsbroadcasts that are multi-segmented and are typically not described indetail in conventionally available information sources because theircontents are typically not known until shortly before broadcast. Inaccordance with embodiments of the invention, the production data usedto produce such programs may be processed to generate metadata for theindividual segments of the program and to distribute that metadata toconsumers in advance of the airing of the program.

A further shortcoming of the conventional technology is that programclassification is limited to broadly defined subject categories that aretypically not easily compared to an individual viewers' personal tastes.For example, conventional technology may be capable of classifyingprograms as being within the category of “sports.” However, for theviewer who is only interested in a particular sport, or a particularteam, such classification is not effective in identifying programs ofparticular interest. Embodiments of the invention address this problemthrough the use of a content classification hierarchy for classifyingthe content of programming events and for defining viewer's particularinterests. The classification hierarchy is comprised of trees of subjectcategories of increasing specificity. This allows programming events tobe classified with a previously unattainable degree of specificity, andallows viewer preferences to be expressed with equal specificity, bothto emphasize particular categories of interest and to exclude categoriesnot of interest. For example, rather than simply being enabled tospecify interest in “sports”, a viewer may specify that he is interestedin football and tennis but not basketball or baseball, and may furtherexpress interest in particular football teams. Thus, devices mayevaluate programming events that are rated according to theclassification hierarchy, using viewer profiles defined according to thesame classification system, and the resulting evaluations reflect actualuser preferences much more accurately than if conventional generalcategories were used. Further, among multiple programs that areevaluated as being of interest to a viewer, the degree of specificity ofthe matches provides a manner of ranking those programs based on viewerpreferences.

The use of hierarchical classification as described above enablesintelligent identification of programming events that will be ofparticular interest to a given viewer. This intelligence may beimplemented to automatically record programming events of interest, toalert a viewer of upcoming programming events of interest, toautomatically display programming events of interest as they becomeavailable, or to selectively provide programs to the viewer. When thisintelligence is coupled with metadata describing individual programsegments as described above, it becomes possible to provide the viewerwith a truly personalized viewing experience, from which alluninteresting subject matter has been eliminated through deep contentspecific filtering at the program segment level.

Further embodiments of the invention may combine the use of a contentclassification hierarchy with keywords for further characterizingprogramming events. Keywords may be given scores to characterize thedegree to which they are descriptive of the programming event. In someembodiments, a keyword may be associated with a category of aclassification hierarchy in a device that analyzes programming events tomore precisely indicate the manner in which the keyword characterizesthe subject matter of interest to the viewer. Related embodiments of theinvention may therefore evaluate programming events using a combinationof keyword matching and category matching.

Further embodiments of the invention may utilize interactive processeswhereby personnel involved in the production of a programming event areenabled to participate in the generation of metadata for the programmingevent through an interactive process, whereby preliminary metadataproduced by a system is either approved or edited to reflect thejudgment of the production personnel as to various aspects such as thecategories used to described the programming event, scores associatedwith the categories, keywords and their scores and categoryassociations, and a title for the programming event.

Further embodiments of the invention may utilize timing data that isinserted in a closed caption data stream to mark at least the beginningsof programming events with precision so that a recording device isenable to determine the beginning of the programming event. The timingdata may be created at the time that the rest of the closed caption datais created for the programming event, and closed caption data includingsuch timing data may be synchronized to the programming event throughtriggering by a teleprompter system. A recording device may use thetiming data to initiate, pause, un-pause and terminate recording.Related embodiments may incorporate such timing data in the video signalitself.

In accordance with one embodiment of the invention, the desirability ofprogramming events may be determined by first receiving metadatadescribing programming events. The metadata for a programming event mayinclude goodness of fit scores associated with categories of aclassification hierarchy, and may also include one or more ofdescriptive data and keyword data. The programming events may then beranked in accordance with the viewing preferences of viewers asexpressed in one or more viewer profiles. The viewer profiles may eachinclude preference scores associated with categories of theclassification hierarchy and may also include one or more keywords.Ranking is performed through category matching and keyword matchingusing the contents of the metadata and the viewer profiles. The viewerprofile keywords may be qualified keywords that are associated withspecific categories of the classification hierarchy. The ranking may beperformed such that qualified keyword matches generally rank higher thankeyword matches, and keyword matches generally rank higher than categorymatches. In alternative embodiments, scores may be calculated such thatthe ranges of scores for qualified keyword matches, keyword matches andcategory matches are overlapping but are generally ordered as previouslydescribed. Related embodiments may pertain to systems that implementsuch methods.

In accordance with a further embodiment of the invention, alertsregarding programming events may be provided to viewers based on theirviewing preferences. A system may receive metadata describingprogramming events. The metadata may include goodness of fit scoresassociated with categories of a classification hierarchy and may furtherinclude one or more of descriptive data and keyword data. Theprogramming events may then be ranked using the metadata based onviewing preferences expressed one or more viewer profiles. An alertschedule may then be determined based on the ranking of the programmingevents. Alerts may then be provided to a viewer based on the alertschedule. Related embodiments may pertain to devices that implement suchmethods.

The following description of various embodiments discloses a variety ofadditional features that may be implemented in conjunction with thevarious embodiments summarized above and in further combinations thatwill be apparent to those having ordinary skill in the art.

BRIEF DESCRIPTION OF THE DRAWINGS

The invention may be better understood with reference to the followingfigures. The components in the figures are not necessarily to scale,emphasis instead being placed upon illustrating the principles of theembodiments of invention described in conjunction therewith.

FIG. 1 illustrates a system for providing metadata and programmingevents to a client device in accordance with an embodiment of theinvention;

FIG. 2 illustrates a process in a system such as the system shown inFIG. 1;

FIG. 3 illustrates an example of production data comprising HTML scriptdata produced by a conventional production application;

FIG. 4 illustrates an example of production data comprising rundown dataproduced by a conventional production application;

FIG. 5 illustrates a system for providing metadata and programmingevents to a client device in accordance with an embodiment of theinvention;

FIG. 6 illustrates a process in a system such as the system shown inFIG. 5;

FIG. 7 illustrates metadata in accordance with an embodiment of theinvention;

FIG. 8 illustrates a portion of a classification hierarchy in accordancewith an embodiment of the invention;

FIG. 9 illustrates a process for generating metadata in accordance withan embodiment of the invention;

FIG. 10 illustrates a process for generating keyword metadata inaccordance with an embodiment of the invention;

FIG. 11 illustrates an interactive process for generating metadata inaccordance with an embodiment of the invention;

FIG. 12 illustrates a client device in accordance with an embodiment ofthe invention;

FIG. 13 illustrates a viewer profile in accordance with an embodiment ofthe invention;

FIG. 14 illustrates a process for producing a preferred programmingevent schedule in accordance with an embodiment of the invention;

FIG. 15 illustrates a process for selectively notifying a viewer of aprogramming event and recording a programming event in accordance withan embodiment of the invention;

FIG. 16 illustrates a process for assigning a desirability score to aprogramming event based on category matching using a viewer profile inaccordance with a preferred embodiment of the invention;

FIG. 17 illustrates a process for assigning a desirability score to aprogramming event based on category matching using multiple viewerprofiles in accordance with a preferred embodiment of the invention;

FIG. 18 shows a process for ranking programming events based on categorymatching and keyword matching in accordance with a preferred embodimentof the invention;

FIG. 19 shows a process for ranking programming events based on categorymatching, keyword matching and qualified keyword matching in accordancewith a preferred embodiment of the invention;

FIG. 20 shows timing data included in a closed caption data stream inaccordance with a preferred embodiment of the invention;

FIG. 21 shows a system for producing closed caption data in accordancewith a preferred embodiment of the invention;

FIG. 22 shows a process in a client device utilizing closed captiontiming data in accordance with a preferred embodiment of the invention;

FIG. 23 illustrates a system for providing programming events inaccordance with an embodiment of the invention;

FIG. 24 illustrates a process in a system such as the system shown inFIG. 23;

FIG. 25 illustrates a system for providing alerts regarding programmingevents to viewers in accordance with an embodiment of the invention; and

FIG. 26 illustrates a process in a system such as the system shown inFIG. 25.

DESCRIPTION OF PREFERRED EMBODIMENTS

In the following description, details of preferred embodiments andcertain alternative embodiments in accordance with the invention are setforth. However, it will be apparent to those of ordinary skill in theart that alternative embodiments of the invention may be implementedusing only some of the features of these embodiments, and usingalternative combinations of the features of these embodiments. Whilevarious operations may be described herein in a particular order and asdiscrete tasks, the order of description should not be construed toimply that the tasks involved in those operations must be performed inthe order in which they are presented or that those tasks must beperformed discretely. Further, in some instances, well known featuresare omitted or generalized in order not to obscure the description. Inthis description, the use of phrases such as “an embodiment,”“embodiments,” “preferred embodiments,” “alternative embodiment” and soforth do not necessarily refer to the same embodiment or allembodiments, although they may.

The following description employs the terms “program,” “program segment”and “programming event.” These terms are used to describe different butrelated concepts. The term “program” is used in the conventional senseof a video program such as a television program. For purposes of thisdescription, a program comprises one or more “program segments” thatpertain to different subjects and therefore can stand on their own ascomplete or individual viewing experiences. Examples of programs thattypically consist of a single programming segment are movies, sit-coms,and sporting events. Examples of programs that are typically comprisedof multiple program segments are news broadcasts, news magazine showsthat present multiple feature stories, sports highlight shows, musicvideo shows, informational shows, home shopping shows, and varietyshows.

The term “programming event” is used in this description to describe adistinct video production presentation that pertains to a particularsubject and therefore stands on its own as a complete or individualviewing experience. Therefore, a given programming event may be asegment of a program, or it may be a whole program if that programconsists of only one program segment.

FIG. 1 provides an overview of a programming event distribution systemin accordance with embodiments of the invention. Referring to FIG. 1, ametadata generator 18 generates metadata 20 that is descriptive of avideo programming event. The metadata generator 18 is typicallyimplemented as a computing device including a processor or processors toexecute programming instructions and memory coupled to the processor(s)and containing programming instructions for instantiating a metadatagenerator system, details of which are described below. The metadata 20is provided by a metadata distributor 22 to a client device 26maintained by a viewer. The client device 26 also receives programmingevents 28 from a programming event provider 24. In various embodiments,the metadata distributor 22 and programming event provider 24 may be asingle entity such as a television broadcasting station or a cable orsatellite television provider. In other embodiments, the metadatadistributor 22 and the programming event provider 24 may be separateentities. For example, the metadata distributor 22 may be an internetserver, whereas the programming event provider 24 may be a televisionbroadcasting station or a cable or satellite television provider. Themetadata 20 provided by the metadata generator 18 is typically receivedby the client device 26 in advance of corresponding programming events28 to allow sufficient time for processing of the metadata in order toevaluate the desirability of upcoming programming events to the viewer.

The metadata generator 18 generates metadata 20 that describesprogramming events in a standard format that may be processed by theclient device 26. Metadata typically comprises delimited data associatedwith fields in a generic metadata format, and typically includes atleast data describing the subject of a programming event and datadescribing the time and duration of the programming event.

The metadata generator 18 may receive as input conventional programdescriptive data (PDD) data 14 that is provided by a commercial PDDprovider 10. Current providers of conventional PDD data are Tribune TV,TV Data, and TV Guide. The conventional PDD data describes televisionprograms through information such as the program title, program starttime, and program duration. PDD data may also include a program subjectdescription if the program is one that is produced, or capable of beingdescribed, significantly in advance of its transmission. Typicalexamples of programming events for which PDD data contains subjectdescriptions include movies, sit-coms, and sporting events.

The metadata generator 18 may also receive production data 16 from aproduction facility agent 12 that obtains the production data fromproduction equipment of a production facility. The production facilityagent 12 is typically implemented as a computing device including aprocessor or processors to execute programming instructions and memorycoupled to the processor(s) and containing programming instructions forinstantiating a production facility agent system, details of which aredescribed below. The production facility agent is preferably implementedon the production facility equipment so as to cooperate with theproduction facility software to obtain production data. Production data16 provided by the production facility agent 12 generally includes datathat is used in the production of a program, such as scripts, cuesheets, schedules, rundowns, closed caption text, teleprompter text,editing information, as so forth. Unlike conventional PDD data,production data used in accordance with the invention includesdescriptive information (scripts, segment titles, segment descriptions,etc.) that is associated with timing information, thus enablingindividual program segments within a program to be identified andindividually described with respect to both their subjects and theirtimes and durations. Thus, production data enables the generation ofmetadata for individual segments of programs, and as a result, programsegments such as individual news stories, variety show skits and soforth may be individually analyzed and provided with their own metadata.

Production data is typically stored in computer systems and may exist ina variety of formats. Examples of conventional software applicationsthat generate production data include the Associated Press ElectronicNews Production System (ENPS), AVID iNEWS NRCS, Avstar, and NewsCenterproduction software. Some such systems may conform to the Media ObjectServer (MOS) protocol, which is commonly used in production facilitiesto provide control of production facility equipment, such astransmission of script data to closed caption generation devices orteleprompter devices.

FIG. 3 shows an example of production data generated by the conventionalENPS system. The production data of FIG. 3 includes script data that isformatted as HTML code. Within the HTML code are individual sectionscorresponding to individual segments of a news broadcast. These segmentsare demarcated by tags having the format <A name=______>, examples ofwhich are highlighted in FIG. 3 for purposes of illustration. FIG. 4shows a further example of production data generated by the conventionalENPS system. The production data of FIG. 4 comprises “rundown” data thatprovides a duration and ending time of individual segments within a newsbroadcast. The rundown data of FIG. 4 is derived from script data, withthe timing for each segment of the program being calculated using anaverage read rate that is specific to the person reading the script forthat segment. The rundown data of FIG. 4 is one example of rundown datathat may be derived from script data, and in alternative forms therundown data may include any other information from the script data.

It will be seen by comparison of FIGS. 3 and 4 that a common set ofidentifiers is used for identifying segments in the script data and inthe rundown data. For example, the segment identified as “125TERROR” inthe HTML script data can be seen in the rundown data to have a totaltime of 2:23 and an ending time of 2:26 into the news broadcast.Although the data in FIGS. 3 and 4 pertain to a program in whichindividual segments are described by single sections in the HTML dataand rundown data, other programs may have individual segments that aredescribed by multiple sections in the HTML data and rundown data, forexample, when the segment consists of multiple distinct “live” and videoportions. Thus the production data of FIGS. 3 and 4 is meant to beexemplary and not descriptive of all production data. Further, theproduction data of FIGS. 3 and 4 is representative only of data producedby one conventional production system, and a variety of other dataformats will be known to those familiar with video productionapplications.

Since production data may exist in a variety of types and formats, it ispreferable that the metadata generator 18 includes a production datastandardization agent that receives production data from the productionfacility agent 12 in its various native formats and processes theproduction data 16 into a standardized delimited form. Alternatively,the production facility agent 12 may provide standardization functions.In the metadata generator 18, the production data 16 is preferablyprocessed together with any available PDD data to generate metadata forindividual programming events.

Processing performed in a metadata generator in accordance withembodiments of the invention is illustrated in FIG. 2. For purposes ofillustration, the tasks performed in the process of FIG. 2 will berelated to the production data of FIGS. 3 and 4. Initially, the metadatagenerator receives production data for a program (30). The productiondata includes timing data and descriptive data for the program, such asis contained in the HTML script data and rundown data of FIGS. 3 and 4.The received production data may be processed to conform to a standarddelimited format, for example, by tagging using an appropriate set ofXML tags. Referring to FIGS. 3 and 4, the HTML data of FIG. 3 may beparsed into script data for individual segments by examining thecontents of delimiting tags such as the <A name=______> tag andextracting all text data associated with the same or relatedidentifiers. Similarly, the rundown data may be parsed into rundown datafor individual segments by searching for delimiting data or charactersand extracting Total and Back Time data associated with the same orrelated identifiers.

The production data is then processed to determine time data ofprogramming events within the program (32). Time data is data thatenables determination of when the segment begins and ends, and maycomprises beginning and ending times, a beginning time and duration, oran ending time and duration. Referring to the rundown data of FIG. 4,time data for segments may be determined through reference to the Totaltime and Back time associated with each identifier. For example, if theprogram represented by FIG. 4 is a 12 noon news program, the ending timeof the segment may be determined by adding the latest Back Time for thesegment to the 12 noon start time of the program, and the starting timemay be determined by subtracting the Total time from the ending time.The production data is also processed to determine descriptive data foreach programming event (33). This may be done before, after, orcontemporaneously with the determination of time data. Descriptive datamay be determined through reference to script data as shown in FIG. 3.For example, keywords and descriptive phrases may be extracted from thescript data. Metadata for the programming events is then generated andstored (34). The metadata for each programming event comprises at leasttime data and descriptive data. PDD data and other types of productiondata may also be processed to generate time data and descriptive data.

Although the process of FIG. 2 was described as occurring within ametadata generator, in alternative embodiments the task of processingthe production data into a standard delimited format for individualprogramming events may be performed by the production facility agent. Insuch embodiments, the production data is provided to the metadatagenerator in a standard delimited form, such as an XML document.

As described with respect to FIG. 1, metadata may be provided toconsumers by a provider of programming events or by an independentmetadata distributor. FIG. 5 illustrates an embodiment of the systemillustrated in FIG. 1 in which programming events occurring within amulti-segment program such as a live local news broadcast are providedthrough a transmission system in common with the programming events. Inthis embodiment, a metadata generator 18 receives production data 16from a production facility agent 12 that obtains production data fromproduction equipment 36 in the production facility where the program isproduced. The metadata generator 18 may be local or remote with respectto the production facility agent 12. In typical implementations, themetadata generator 18 is connected to the production facility agent 12through a data network such as a LAN, WAN, or the internet. The metadatagenerator 18 may also receive PDD data 14 from an PDD provider 10. PDDdata may likewise be received through a data network. The metadatagenerator 18 generates metadata 20 for each segment of the program fromthe production data, and optionally also from the PDD data. Metadata 20for each programming event within the program may then be provided fromthe metadata generator 18 to the production facility agent 12, where itmay be provided for transmission in common with programming eventsthrough a transmission system 38, such as RF airwaves or cable orsatellite distribution systems, for reception by a client device 26. Themetadata may then be transmitted to client devices, in the case of aproduction facility agent at a broadcast production facility locationsuch as a local television station. Alternatively, the metadata may beprovided to a distribution agent 35 that transmits the metadata througha transmission system 38 independently of the transmission ofprogramming events from the production facility. The distribution agentmay be located, for example, at a cable system head end.

A variety of coding standards may be used for encoding the metadata,such as the Harris Communication, Divicom, and NDS standards. Metadatamay be transmitted in the vertical blanking interval of the videosignal. Alternatively, where programming events are broadcast usingMPEG-2 digital video, the metadata may be encoded in the text portiondefined by the MPEG-2 standard. In cable televisions applications, it ispreferable to transmit the metadata by out of band signaling, such as byusing the separate band reserved for data transmission to a separatetuner of the cable receiver, as is conventionally used for services suchas viewing authorization. In satellite television applications, it ispreferable to provide the metadata by in band multiplexing.

The metadata for a given programming event is preferably transmittedsufficiently in advance of corresponding programming events to allowtime for processing of the metadata by client devices. However, it maybe desirable to limit the amount of advance time where client metadatastorage capacity is limited. For example, in the case of programs havinga large number of constituent programming events, such as news programs,it may be preferable to send metadata no more than one hour in advanceof the program.

Processing occurring in the production facility agent of FIG. 5 isdescribed in FIG. 6. In accordance with FIG. 6, the production facilityagent provides production data for a program to a metadata generator(40). The production data typically includes descriptive informationthat is associated with timing information, such as the data illustratedin FIGS. 3 and 4. The production facility agent then receives metadatafor individual programming events within the program (42). Theproduction facility agent then provides the metadata for transmissionthrough a programming event transmission system (44). The metadata mayencoded using an encoding standard such as described above.

FIG. 7 shows an example of a logical organization of metadata for aprogramming event in accordance with preferred embodiments of theinvention. The illustrated metadata describes a segment of a local newsbroadcast relating to an NFL team. The metadata is comprised ofdelimited descriptive data associated with fields of a generic metadataformat. A Program_ID field provides a unique identifier for eachprogramming event. A Program_Name field provides the name of the programwith which the programming event is associated. A Program_Descriptionfield provides a description of the programming event, and aProgram_Reduced_Description field provides a shortened description or“gist” of the programming event. Fields for Program_Date,Program_Start_Time and Program_Duration provide information identifyingwhen and for how long the programming event is aired. A Channel_ID fieldidentifies the channel on which the programming event will be received.A Program_Type field describes the type of programming event, such as aprogram, a program segment, or a movie. Program_TV_Rating andProgram_MPAA_Rating fields provide ratings assigned to the program byrating services. A Message_Status field indicates whether theprogramming event is a first transmission, a retransmission, or anupdated transmission. A Category_List field provides goodness of fitscores for the programming event with respect to categories in aclassification hierarchy as described further below. A Keyword_Listfield contains keywords describing the subject matter of the programmingevent and may further contain goodness of fit scores for each keyword.The metadata is preferably formatted in a standard delimited format, forexample, as an XML document using appropriate tags.

The classification hierarchy with respect to which the programming eventis scored comprises a hierarchy of subject categories. FIG. 8illustrates a portion of an exemplary classification hierarchy inaccordance with embodiments of the invention. At the top level of thehierarchy are general subject categories such as Sports, Entertainment,News, etc. Extending from each of the top level categories is a tree ofmore specific subject categories that fall within the top levelcategory. FIG. 8 particularly illustrates a branch within the hierarchyin which Football is one of several categories within Sports, NFL is oneof several categories within Football, AFC is one of several categorieswithin NFL, and Buffalo Bills is one of several categories within AFC.

In the classification hierarchy of FIG. 8, the categories are shown asbeing organized in common ordinal levels, such that all categories atthe top level of the hierarchy are at Level 1, all categories dependingfrom Level 1 categories are at Level 2, and so forth. Embodiments of theinvention may treat the common ordinal level of a category as beingrepresentative of that category's specificity relative to othercategories of the classification hierarchy. However, since the degree ofspecificity of categories at a given ordinal level may vary amongbranches of the hierarchy, alternative embodiments may representspecificity in other manners. For example, each category may be assignedindividual specificity scores, or all categories depending from a givencategory in the hierarchy may be commonly assigned a particularspecificity score.

In accordance with preferred embodiments of the invention, metadatagenerators such as those of FIGS. 1 and 5 produce metadata such as shownin FIG. 7 by processing descriptive data concerning a given programmingevent to classify the subject of the programming event using aclassification hierarchy such as the one shown in FIG. 8. An example ofprocessing performed by a metadata generator to produce metadata for aprogramming event in accordance with an embodiment of the invention isillustrated in FIG. 9. Initially, the metadata generator receives datafor analysis that relates to a programming event (50). The received datamay include PDD data and production data. Where the received data isproduction data, that data is preferably processed by a standardizationagent that converts the production data to a standard delimited formatfor further processing. The data may also be parsed to determineindividual programming events within a program. The data is thenanalyzed and a goodness of fit score for the programming event isassigned with respect to each category of the classification hierarchy(52). A goodness of fit score indicates how well the particular categorydescribes the subject matter of the programming event. Goodness of fitscores may be generated using an appropriately configured classificationapplication. For example, the InterMedia media searching tool producedby Oracle Corporation, or the K2 classification tool produced by VerityCorporation, may be configured to define a thesaurus reflecting words,phrases and concepts associated with the categories of theclassification hierarchy, such that PDD and production data for aprogramming event may be searched with respect to each category of thehierarchy to generate a list of matched categories with associatedconfidence scores in a range from 1% to 100%. The confidence score foreach matched category is used as that category's goodness of fit score,and categories having no match are treated as having goodness of fitscores of zero.

After assigning goodness of fit scores (52), the metadata generatordetermines a set of categories within the hierarchy that arerepresentative of the programming event (54). In the preferredembodiment, the metadata generator first determines for each branch ofthe classification hierarchy the most specific category that hasnon-zero goodness of fit score. For example, referring to theclassification hierarchy of FIG. 8, if the category Buffalo Bills isassigned a goodness of fit score of 75%, the higher level categories inits branch will also have non-zero goodness of fit scores; however,Buffalo Bills is the most specific category having a non-zero score inits particular branch of the hierarchy. The metadata generator thendetermines additional representative categories by examining thedifferences in the goodness of fit scores of the most specificcategories and their parent categories. In preferred embodiments, theparent category of a most specific category is determined to be anadditional representative category if the difference between its scoreand the most specific category exceeds a predetermined amount orpercentage. Determination of such parent categories serves to identifyinstances in which it is desirable to supplement or qualify therepresentative information conveyed by the score of a most specificcategory. It may also be preferable to limit the number of categoriesper programming event by defining a maximum number of categories perprogramming event and utilizing the categories with the highest scoresconsistent with that maximum number. It may further be preferable toutilize a score thresholding procedure whereby a minimum goodness of fitscore is required for a category to be included in the metadata.

Once determined, the identifiers and associated goodness of fit scoresof the representative categories are stored in delimited fashion (56).Other data is also generated through processing of the PDD andproduction data and is stored together with the goodness of fit scoresin delimited fashion to comprise metadata for the programming event. Theother data referred to here may comprise data such as is shown in theexemplary metadata of FIG. 7, such as description, time, duration,keywords, etc. Like categories, keywords may be assigned goodness of fitscores using a classification application. A variety of storage formatsare available for storing the metadata. For example, the metadata may bestored as an XML document using appropriate tags for indicating thevarious types of data within the metadata.

In further preferred embodiments, the metadata generator mayadditionally provide automatic generation of keywords. Keywords arepreferably generated through analysis of descriptive data included inany production data and PDD data that is available for the programmingevent. In one preferred embodiment, all text data associated with theprogramming event such as script data and PDD data is processed toidentify all verbs and all nouns and associated adjectives containedtherein. These candidate keywords are then provided as input to thecategorization tool, which produces a goodness of fit score for eachcategory of the classification hierarchy based on each input candidatekeyword. Keywords are then chosen from among the candidate keywordsbased on the highest goodness of fit score associated with eachcandidate. To provide further precision, the category goodness of fitscores for each candidate keyword may be correlated with the categorygoodness of fit scores for the programming event as a whole, so thatcandidates having high goodness of fit scores for categories that arenot relevant to the programming event as a whole are not chosen askeywords. The highest category goodness of fit score for each chosenkeyword may be adopted as a goodness of fit score for the keyworditself.

In one alternative to the aforementioned preferred embodiment,processing of the descriptive data to determine nouns and verbs may beeliminated and all words from available script data may be provided ascandidate keyword inputs to the classification tool. In this alternativeembodiment it is preferred to correlate the resulting category scores ofeach candidate keyword with the category scores of the programming eventas a whole.

A process encompassing the aforementioned preferred embodiment, itssuggested alternatives and other alternative implementations isillustrated in FIG. 10. As shown in FIG. 10, candidate keywords aredetermined (220) from descriptive data associated with a programmingevent. The candidate keywords are provided (222) as input to aclassification tool configured to generate goodness of fit scores forcategories of a classification hierarchy. Keywords are then selected(224) from among the candidate keywords based on the category goodnessof fit scores generated for each of the candidate keywords by theclassification tool. The selected keywords are then stored (226) as acomponent of metadata for the programming event.

In a further preferred embodiment, the metadata generator mayadditionally provide automatic generation of titles for programmingevents. This embodiment is particularly preferred for applications inwhich the programming event comprises a segment of a larger program, forexample, an individual segment of a news program. In accordance with thepreferred embodiment, the metadata generator generates a title for theprogramming event through analysis of the production data. For example,the title may comprise the name of the category having the highestgoodness of fit score in the metadata, combined with one or more of thehighest scoring keywords. Alternatively, the classification tool thatgenerates category goodness of fit scores may be further configured toproduce a summary of the programming event using the descriptive data.In further alternatives, a most descriptive noun, action word, or phrasemay be selected from the descriptive data.

As an enhancement to the aforementioned embodiments, a further preferredembodiment may implement an interactive process whereby a producer of aprogramming event is enabled to select or specify categories, keywords,and goodness of fit scores to be included in the metadata for theprogramming event. FIG. 11 shows process flow in a system in accordancewith this preferred embodiment. Initially the system generates (228)preliminary metadata for the programming event. The preliminary metadatais typically generated from production data and PDD data using aclassification tool in the manner described herein, and typicallycomprises categories and category goodness of fit scores, keywords andkeyword goodness of fit scores, and a title. The preliminary metadata isthen provided (230) to a system user, typically a producer or otherperson involved with production of the programming event. Thepreliminary metadata is preferably provided using a graphical userinterface that displays the various components of the preliminarymetadata and enables the system user to change the preliminary metadataor to add additional metadata. For example, the system user ispreferably enabled to delete a category, add a category, and add orchange a category goodness of fit score. Similarly, the system user ispreferably enabled to add or delete keywords, to change keyword goodnessof fit scores, and to edit titles and other descriptive components ofthe preliminary metadata. Thus by operation of the user interface, thesystem receives (232) specified metadata from the system user responsiveto the preliminary metadata. The specified metadata, or at least theportions of the metadata that were specified by the system user, arethen utilized by the metadata generator in preference to any conflictingmetadata that may be later generated by the classification application.In one alternative to these embodiments, the system user may simplyapprove the preliminary metadata provided by the system. This approvalmay be provided separately for the different metadata components such ascategories, category goodness of fit scores, keywords, keyword goodnessof fit scores, and title.

The aforementioned embodiments may be implemented in a variety ofmanners in accordance with the particular application. In oneimplementation, the user interface is generated by the productionfacility agent, while the preliminary metadata is generated by a remotemetadata generator with which the production facility agent interacts.The production facility agent may be implemented independently of otherapplications running on the production facility equipment, or it may beimplemented through macros or extensions associated with otherproduction equipment applications. Alternatively, the metadata generatormay be implemented locally as part of the production facility agent oras a separate agent running on the production facility equipment.

In further alternative embodiments it may be desirable for businesspurposes to adjust the goodness of fit scores for particular programmingevents before they are stored in metadata. For example, goodness of fitscores may be raised so that that analysis of the goodness of fit scoreswill be biased in favor of those programming events as compared to otherprogramming events.

As described above with respect to FIGS. 1 and 5, metadata forprogramming events may be distributed to client devices, where it maythen be processed by a client device to automatically determineprogramming events that are desirable for viewing or storage. The clientdevice is preferably a video storage device that is used in associationwith a video display device such as a television for reception, displayand storage of video. However, embodiments of the invention may beimplemented in a variety of other types of client devices including settop boxes, personal computers, video display devices such astelevisions, wireless communication devices, and personal digitalassistants.

Client devices in accordance with embodiments of the invention arecomprised of a data processing device that includes a processor orprocessors and memory storing one or more viewer profiles, receivedmetadata, and programming instructions that instantiate a client agentthat processes metadata to determine programming events that aredesirable for viewing or storage in accordance with the viewer profiles.FIG. 12 shows a client device in accordance with a preferred embodimentof the invention. In this preferred embodiment, the client devicereceives video signals from a broadcast, cable or satellite televisionprovider, data network, or other video source, and receives metadatafrom a distinct metadata distributor such as an internet server. Theclient device includes a video receiver 60 for receiving anddemodulating signals representing programming events 62. Typically thevideo receiver is a device for demodulating analog or digital videosignals. The client device further includes a metadata receiver 64 forreceiving metadata 66. Typically the metadata receiver is a device thatis capable of communicating with a network for downloading metadatafiles to the client device. For example, the metadata receiver may be amodem that is programmed to periodically access a remote server wheremetadata is stored. The client device further comprises a data processor68 such as a microprocessor, a data storage device 70 such as a RAM orROM or a combination of the two, and a bulk data storage device 72 suchas hard disk storage or optical disk storage. A display interface 74generates audio and video signals 78 for use by a display device such asa television. The video receiver 60, metadata receiver 64, dataprocessor 68, data storage 70, bulk data storage 72, and displayinterface 74 are coupled through a bus 76.

As noted above, it is assumed for the preferred embodiment shown in FIG.12 that the client device receives video signals from a broadcast, cableor satellite television provider, or data network and receives metadatafrom a distinct metadata distributor such as a dial-up server, andtherefore has separate video and metadata receivers. However, inalternative embodiments, both the metadata and programming events may bereceived by a single receiver. For example, metadata may be transmittedin broadcast provided through broadcast or cable television channels, ormay be provided in a text band of a digital video signal such as isprovided in the MPEG-2 digital video standard. Alternatively, video andmetadata may be provided from a common source through a commontransmission medium, but received by separate receivers in the clientdevice, as is the case in preferred cable television receiverembodiments.

Client devices in accordance with preferred embodiments of the inventionprovide standard PDD information and standard tools such as a programgrid and keyword searching to allow users to manually identify programsfor viewing or recording. In addition, client devices in accordance withpreferred embodiments of the invention analyze metadata to determinedesirable upcoming programming events, and may automatically recordthese programming events, alert the viewer to these programming events,or automatically display these programming events. The desirability of aprogramming event is determined with respect to viewer preferencesrepresented in one or more viewer profiles stored in the client device.An example of a viewer profile in accordance with preferred embodimentsof the invention is provided in FIG. 13. In this viewer profile, aProfile_ID field provides a unique identifier for the profile. AProfile_Name field provides a name for the profile as it will be knownto viewers. A Profile_Description field provides a longer descriptionthat may be used to provide more detail about the types of programs thatthe profile is intended to identify. A Profile_Priority field provides anumber that indicates the priority of the profile relative to otherprofiles stored in the client device. A Profile_Alerts_Per_Hour fieldprovides a number of times per hour that an alert is provided to theviewer indicating that a program providing a better fit than the onebeing viewed is currently available for viewing. AProfile_Alert_Minutes_In_Advance field specifies an amount of time priorto a programming event that a viewer is to be notified of a programmingevent. A Profile_Activation_Time indicates a time frame during which theprofile should be used for analyzing programs. A Category_Scores fieldcontains an identifier and associated preference score for categories ina classification hierarchy for which a preference score has beenspecified. The preference scores represent a relative degree of interestin each category that may be used in processing of metadata to determinethe relative desirability of programming events using their categorygoodness of fit scores. In the preferred embodiment, a preference scoreof ten indicates the highest level of preference. A Keyword_List fieldcontains keywords that reflect the viewer's viewing tastes. A keywordmay be associated with a category of the classification hierarchy,indicating that the keyword reflects the viewer's viewing tastesspecifically with regard to subject matter falling within that category.For example, in FIG. 13, the keyword “Bills” is associated with thecategory Sports/Football/NFL. Such keywords are referred to herein asqualified keywords. Qualified keywords allow the viewer to effectivelydefine a subset of subject matter within a category that is ofparticular interest. Keywords may also be assigned preference scores, asshown in FIG. 12. As with categories, keyword preference score may beused in processing of metadata to determine the relative desirability ofprogramming events using keyword matching. A variety of storage formatsare available for storing the viewer profile. For example, the viewerprofile may be stored as an XML document using appropriate tags forindicating the various types of data within the viewer profile.

The client device is preferably provided with generic viewer profilesthat are tailored to different viewing interests such as sports,political news, and other interests. The generic profiles may bepre-programmed in the client device or may be provided to the clientdevice by the metadata distributor. The user is preferably enabled tomodify or delete the pre-programmed viewer profiles and to configureadditional viewer profiles in accordance with particular viewing tastes.

Accordingly, the client device is provided with programming instructionsfor providing an editor enabling the user to create and edit viewerprofiles. The profile editor provides a graphical user interface thatincludes tools enabling a user to enter the types of information thatmay be included in a viewer profile such as the one illustrated in FIG.13. In particular, the viewer may enter information such as the profilename, description and priority, alerts per hour or other period of time,alert minutes in advance or time in advance, profile activation time,and keywords. In addition, the viewer may enter scores for each categoryin the classification hierarchy, may associate keywords with categoriesof the classification hierarchy as qualified keywords, and may associatepreference scores with keywords and qualified keywords. The userinterface preferably allows the user to navigate through theclassification hierarchy structure and to enter scores for categories asdesired. When a preference score is entered for a given category, thatpreference score is preferably assigned to all subcategories of thegiven category. In other words, all categories that branch from thegiven category are assigned the same preference score as the givencategory. Therefore, if a category is given a preference score of ten,all of its subcategories will likewise be given a preference score often. Similarly, if a category is given a preference score of zero, allof its subcategories are likewise given a score of zero. Of course, thescores for those subcategories can later be changed individually.

Viewer profiles may be used in processing metadata to build a scheduleof desirable programming events that may be automatically recorded,recommended for viewing, or switched to automatically. A schedulebuilding process in a client device in accordance with preferredembodiments is illustrated in FIG. 14. This process assumes thatmetadata for various programming events becomes available sporadically,and the process therefore involves periodic updating to account for anynewly available metadata. Initially, all available metadata for upcomingprogramming events is received (100). The metadata may be received byconnecting to a server and downloading new metadata. Alternatively,metadata may be continuously received through the broadcast system thatprovides programming events. The metadata is then processed inaccordance with one or more viewer profiles to assign desirabilityscores to each programming event (102). The scores of the programmingevents along with their times and durations are then processed todetermine a preferred programming event schedule (104). In the case of arecording schedule in a device capable of recording only one programmingevent at a time schedule reflects the most desirable non-overlappingavailable programming events. In contrast, in the case of an alertschedule, the programming events may overlap, since the viewer candecide which programming events to watch. In each instance, the clientdevice preferably stores at least the programming event title, time,duration, and category, and the viewer profile or profiles that resultedin its selection. Generation of the schedule may include a thresholdingfunction whereby a programming event must achieve a minimum desirabilityscore in order to be included in the schedule. Other functions, such asfiltering out programming events that have already been recorded orviewed, may also be performed. After the schedule is determined, aperiodic updating of the schedule is performed. Particularly, after agiven time interval, additional metadata is received (106). Theadditional metadata typically corresponds to programming events forwhich no metadata was previously received, but updated metadata may alsobe received. The additional metadata is processed to determinedesirability scores for corresponding programming events (108). Thescores, times and durations for those programming events are thenprocessed to determine any updates to the preferred programming eventschedule (110). An alert list may be updated whenever a new programmingevent score is determined to be higher than one already stored in theschedule. A recording schedule may be updated when a new programmingevent score is determined to be higher than another programming event inthe same time slot that is already stored in the schedule, or when a newprogramming event with a sufficiently high score occurs in a time slotfor which there is no programming event listed in the schedule. Afterdetermining any updates, the updates are stored in the preferredprogramming event schedule (112). The updating process is then repeatedat intervals.

Since metadata is assumed to arrive sporadically and may arrive onlyshortly prior to the time of its corresponding programming event, it ispreferable to prioritize the processing of available metadata on thebasis of the time remaining until the beginning of the correspondingprogramming event. This may be determined through reference to time datacontained within the metadata.

In conjunction with the scheduling process, the viewer is preferablynotified each time a programming event is added to the schedule, andenabled to approve or decline each programming event. This may beaccomplished by displaying an icon that may be operated by the viewer todisplay information about a newly scheduled programming event. Scheduledprogramming events that have been explicitly approved by the viewer maybe treated in the updating process as having a highest possibledesirability score, irrespective of the actual score, such thatconflicting programming events that have higher scores but were notidentified prior to the viewer's approval cannot be substituted in theschedule without explicit viewer approval. In further preferredembodiments of the invention, the user is enabled to manually edit thepreferred programming event schedule and to manually scheduleprogramming events for recording. Like viewer-approved programmingevents, manually scheduled programming events are given priority overlater-identified preferred programming events.

In preferred embodiments of the invention, the preferred programmingevent schedule may be used by the client agent to provide alertsconcerning programming events to a real time viewer, or to automaticallyrecord programming events when no real time viewer is present. A controlprocess performed by the client agent in accordance with preferredembodiments of the invention is shown in FIG. 15. In the illustratedprocess, it is assumed that the client device includes two RF tunersenabling a real time viewer to receive a first channel for viewing whilea second channel may also be received for recording. Initially, theclient agent checks the schedule to determine a next upcoming preferredprogramming event (120). The client agent then determines whether a realtime viewer is present (122). If no viewer is present, the preferredprogramming event is recorded (124), for example, by storage in the bulkdata storage device as illustrated in FIG. 12. Alternatively, if thereis a real time viewer, the viewer is provided with an alert for theupcoming preferred programming event (126). Alerts may be provided invarious manners, such as by generating an audible tone or displaying abanner on the video display device. The time of the notification may bedetermined with reference to the value in theProfile_Alert_Minutes_In_Advance field of a viewer profile as shown inFIG. 13. If the viewer selects the preferred programming event forviewing (128), the preferred programming event is automaticallydisplayed as soon as it is available for viewing (130). On the otherhand, if the viewer does not select the preferred programming event forviewing, the preferred programming event is recorded (124). Inalternative embodiments where the client device includes only one RFtuner, the decision by a real time viewer not to view something otherthan the preferred programming event causes the recording of thepreferred programming event to abort. Newly recorded programs arepreferably identified in a notification list that may be accessed by theviewer. The notification list may be cleared after each access by theviewer.

Recorded programming events are preferably indicated in a recordedprogram list from which the user is enabled to select recordedprogramming events for viewing. Information stored in association witheach programming event in the recorded program list preferably includesthe time and date of the programming event, the programming event score,the profile that selected the programming event for recording, and thecategory of the programming event. A user is preferably enabled to sortthe recorded program list in accordance with any of these categories ofinformation. The device also preferably provides the option of seamlessreplay of the recorded programming events in an order chosen inaccordance with one of the above categories of information.

In one preferred embodiment of the invention, the client devicecomprises a set top box such as a cable box. The set top box analyzesmetadata and generates a schedule of programming events that matchviewer preferences. The set top box further provides on-screen alerts inadvance of each programming event in the schedule. The on-screen alertis preferably available in multiple styles that may be chosen by theuser, such as an icon or an information banner. The banner may containinformation such as the programming event title, a description, anindication of categories or keywords matched, and the channel number oridentifier. A particular category matched, or the fact of a keywordmatch, may be indicated by an icon displayed within the alert banner. Inone preferred embodiment, the banner includes the matched categorygenerating the highest match score, the matched keyword generating thehighest match score, and the associated scores. The banner is alsopreferably provided in different colors that correspond to the viewerprofile that generated the alert. The user is preferably enabled toconfigure the default amount of time that the alert is displayed, toclear the alert from the screen, and to switch to the programming eventof the alert automatically. The user is also preferably enabled to viewthe alert list and to delete programming events from the alert list.

The alert list is preferably viewable by the viewer, and preferablyallows the viewer to delete programming events from the alert list, andto confirm interest in programming events in the alert list so thatsubsequently analyzed programming events with higher scores do not causethose programming events to be bumped from the list. The alert list ispreferably generated in a manner that provides a maximum number ofalerts within a given time period, such as a fixed number of alerts perhour. This parameter may be configured as part of a viewer profile, asshown in FIG. 13. The alert list preferably highlights any programmingevents in the list that are currently showing. The alert list ispreferably limited to those channels that the client device is capableof receiving.

As noted above, the client device may determine preferred programmingevents with respect to one or more viewer profiles. In the case wherealerts are provided, it is preferable that the viewer profiles used bythe client device to identify programming events correspond to thepreferences of the actual real time viewers. Accordingly, the clientdevice may enable a real-time viewer to specify one or more viewerprofiles to be used for generating alerts during the viewer's viewingsession. For example, the viewer may select a particular viewing profiletailored to his tastes while excluding profiles of other viewers who arenot present, or the viewer may select a group viewer profile thatreflects the collective tastes of present viewers. In alternativeembodiments, upon detection of a real time viewer, such as by detectingactivation of the video display device or changing of channels, suchprofiles may be automatically selected by the client device based onindicators of the current real time viewer such as channel selectionpatterns. In view of these considerations, embodiments that provide bothreal time viewer alerts and automatic recording may preferably maintaina first preferred programming schedule for recording purposes based onthe full set of viewer profiles maintained by the client device, and mayfurther generate a second preferred programming schedule in accordancewith profiles specific to the real time viewer as described above forpurposes of providing alerts. In such embodiments, conflicts between thetwo programming schedules are resolved in favor of the real time viewerwhere only a single receiver is available.

The task of determining desirability scores for programming events isperformed using the metadata for a programming event and one or moreviewer profiles stored in the client device. In preferred embodiments ofthe invention, scores are determined in a manner that gives preferenceto keyword matches over category matches. Thus, for example, where aviewer's keyword matches a keyword contained in the keyword field of themetadata, or matches a word contained in the description field of themetadata, that programming event may be assigned the maximum preferencescore irrespective of any preference score generated using theprogramming event's category goodness of fit scores. Further scoringmethods using a combination of keyword and category matching aredescribed below.

A process for determining a desirability score for a programming eventbased on metadata category goodness of fit scores and viewer profilecategory preference scores in accordance with a preferred embodiment ofthe invention is shown in FIG. 16. Referring to the left-hand column ofFIG. 16, the process first determines each category of theclassification hierarchy that has a goodness of fit score in themetadata and that is assigned a preference score in the viewer profile(140). These categories are referred to herein as matched categories.For purposes of this determination, a category having a preference scorethat is equal to zero or less than a threshold minimum score may betreated as not having a preference score, and thus the category will notbe considered a matched category. For each matched category, a score isdetermined (142). The score is a function of the goodness of fit scoreof the matched category and the preference score of the matchedcategory. The score may be weighted in accordance with the specificityof the matched category so that the score increases with the specificityof the matched category. After scores for each matched category aredetermined, the highest score and the category generating the highestscore are adopted as the desirability score and category of theprogramming event (144).

The function and weighting scheme for generating scores may beimplemented in a variety of manner. For example, in an implementation inwhich the categories of the classification hierarchy are assignedindividual specificity weights that increase with the specificity of thecategory, the score may be calculated as a function of the goodness offit score, the preference score, and the specificity weight of thematched category. In this manner, the score is influenced by thepreference encoded by the viewer in the profile for the matchedcategory, the degree to which the programming event is described by thematched category, and the specificity with which the matched categorydescribes the subject matter of the programming event.

In accordance with a preferred embodiment of the invention, a score iscalculated as illustrated in the right-hand column of FIG. 16. In thispreferred embodiment, the categories of the classification hierarchy arearranged in common ordinal levels, and the level of a category is takenas being representative of its specificity. Thus, in accordance with thepreferred embodiment of FIG. 16, the score for a given matched categoryis calculated by first weighting the preference score of each categoryin the branch terminating with the matched category by a factor that isbased on the level of the category (146). In the preferred embodiment,this weight is calculated as the quantity e^(N−i), where N is the numberof ordinal levels in the classification hierarchy and i is the ordinallevel of that particular category. The weighted preference scores forall of the categories in the branch are then summed, and the sum ismultiplied by the goodness of fit score of the matched category (148).This sum is then weighted in accordance with the duration of theprogramming event (150), for example, by multiplying the score by 10,000and adding the duration in seconds of the programming event. Weightingof the score by the program duration serves to resolve conflicts amongoverlapping programming events that would otherwise have identicalscores. The score for each matched category is therefore calculated as:$\left( {10^{4}*S*{\sum\limits_{i = 1}^{N}\quad{{P\left( V_{i} \right)}*{\mathbb{e}}^{N - i}}}} \right) + d$where:

-   N=the number of ordinal levels in the classification hierarchy-   V_(i) 32 a category in the branch of the matched category at level i    of the hierarchy-   P(V_(i))=the preference score of category V_(i) in the viewer    profile-   S=the goodness of fit score of the matched category-   d=the duration of the programming event in seconds

In further preferred embodiments, the category preference scores ofmultiple viewer profiles may be used for determining desirability scoresfor programming events. A process for determining a desirability scorefor programming events in accordance with a preferred embodiment isshown in FIG. 17. This embodiment is particularly preferred forgenerating scores to be used in determining a recording schedule thataccounts for the combined preferences expressed in more than one viewerprofile. Referring to the left-hand column of FIG. 17, the process firstdetermines each category that has a goodness of fit score in themetadata and that is assigned a preference score in a viewer profile(160). These again are referred to as matched categories, and may omitany categories having a preference score less than a certain minimumvalue. For each matched category, a score is determined (162). The scoreis a function of the goodness of fit score of the matched category, thepreference score assigned to the matched category in each viewerprofile, and a priority of each viewer profile. The score may beweighted in accordance with the specificity of the matched category sothat the score increases with the specificity of the matched category.After scores for each matched category are determined, the highest scoreand the category generating the highest score are adopted as thedesirability score and category of the programming event (164).

The function and weighting scheme for generating scores may beimplemented in a variety of manner. For example, in an implementation inwhich the categories of the classification hierarchy are assignedindividual specificity weights that increase with the specificity of thecategory, the score may be calculated as the sum of quantitiescalculated for each profile, where that quantity is the product of thegoodness of fit score, the preference score, a quantity proportional tothe priority of the viewer profile, and the specificity weight of thematched category. In this manner, the score is influenced by thepreference encoded by the viewer in each profile for the matchedcategory, the degree to which the programming event is described by thematched category, the priority of each profile that included a score forthe matched category, and the specificity with which the matchedcategory describes the subject matter of the programming event.

In accordance with a preferred embodiment of the invention, the score iscalculated as illustrated in the right-hand column of FIG. 17. In thispreferred embodiment, the categories of the classification hierarchy arearranged in common ordinal levels, and the level of a category is takenas being representative of its specificity. Thus, in accordance with thepreferred embodiment of FIG. 17, the score for a given matched categoryis calculated by first weighting the preference score of each categoryin the branch terminating with the matched category by a factor that isbased on the level of the category (166). This is done for each profilethat includes a preference score for the matched category. In thepreferred embodiment, this weight is calculated as the quantity e^(N−i),where N is the number of ordinal levels in the classification hierarchyand i is the ordinal level of that particular category. The weightedpreference scores for all of the categories in each branch are thensummed for each profile, and these sums are multiplied by the goodnessof fit score of the matched category (168). Each of these products isthen weighted in accordance with the priority of its profile. In thepreferred embodiment, a quantity P is associated with each priority,such that P is greater for higher priority. The weight for a givenprofile j may then be calculated as the quantity P_(j) divided by thesum of all Ps corresponding to all profiles having a preference scorefor the matched category. After priority weighting the product for eachprofile (170), the priority weighted products are summed together andmultiplied by the number of profiles that include a preference score forthe matched category (172). This sum is then weighted in accordance withthe duration of the programming event (174), for example, by multiplyingthe score by 10,000 and adding the duration in seconds of theprogramming event. The score for each matched category is thereforecalculated as:$\frac{10^{4}*S*{I}*{\sum\limits_{j = 1}^{I}\quad{P_{j}\left( {\sum\limits_{i = 1}^{n}\quad{{P\left( V_{ij} \right)}*{\mathbb{e}}^{N - i}}} \right)}}}{\sum\limits_{j = 1}^{I}\quad P_{j}} + d$where:

-   N=the number of ordinal levels in the classification hierarchy-   V_(i)=a category in the branch of the matched category at level i of    the hierarchy-   P(V_(ij))=the preference score of category V_(i) in profile j-   P(j)=a quantity representing the priority of Profile j-   |I|=number of profiles that include a preference score for the    matched category-   S=the goodness of fit score of the matched category-   d=the duration of the programming event in seconds

In contrast to the aforementioned multiple viewer profile embodiment, itis sometime preferable to calculate scores for viewer profilesindividually rather than in a combined manner as discussed above. Forexample, for providing alert lists for multiple viewer profiles, it isdesirable to normalize the number of alerts generated by each profile.Thus in such embodiments it is preferred to calculate the scores foreach profile separately and allot a given number of alerts to eachprofile.

In alternative preferred embodiments, desirability scores may bedetermined through a combination of keyword and category matching toproduce results that satisfy the viewer's preferences with greaterreliability. For purposes of describing these alternative embodiments,desirability scores determined based upon category matching as describedabove will be referred to as category match scores, while desirabilityscores based upon keyword matching will be referred to as keyword matchscores or qualified keyword match scores, as discussed further below.

In a first alternative preferred embodiment, simple keyword matching maybe employed in combination with category matching to rank programmingevents. In this alternative embodiment, a simple keyword match between akeyword of a viewer profile and a metadata keyword or a word included indescriptive data of the metadata produces a keyword match score. Akeyword match preferably encompasses both exact matches between keywordsand matches between roots of keywords. The keyword match score assignedto a simple keyword match is preferably chosen to be greater than amaximum category match score, so that any programming event having akeyword match is ranked higher than any programming event not having akeyword match. This reflects a presumption that a programming eventmatching a keyword provided by a viewer is more likely to satisfy theviewer's preferences than a programming event matching the viewer'sspecified categories. Of course, alternatives to the present embodimentmay implement different scoring reflecting different presumptions.

The keyword match score may be a constant that is assigned for eachkeyword match. Alternatively, the keyword match score may be a constantthat is augmented by an additional quantity that is programming eventdependent to thereby minimize the possibility of equal ranking resultingfrom more than one keyword match. For example, a constant used as abasic keyword match score may be augmented by a quantity that is derivedfrom the length of the programming event, or a preference scoreassociated with the keyword in the viewer profile that produced thekeyword match, or a category match score determined for the programmingevent using the category preference scores of the viewer profile thatproduced the keyword match.

A basic process in a client device encompassing the first alternativepreferred embodiment and various implementations thereof is illustratedin FIG. 18. Initially metadata is received (234). The metadata describesprogramming events, and includes goodness of fit scores associated withcategories of a classification hierarchy. The metadata further includesat least one of descriptive data, such as is illustrated in theProgram_Description and Program_Reduced_Description fields of themetadata of FIG. 7, and keyword data, as illustrated in the Keyword_Listfield of FIG. 7. After receiving metadata, the programming events areranked (236) in accordance with viewer preferences expressed in one ormore viewer profiles. The viewer profiles include preference scoresassociated with categories of the classification hierarchy and one ormore keywords. The ranking uses the metadata goodness of fit scores andthe viewer profile category preference scores to determine categorymatches and uses the metadata descriptive data and/or keyword data andthe viewer profile keywords to determine keyword matches.

In a second alternative preferred embodiment, qualified keyword matchingmay be employed in combination with simple keyword matching and categorymatching to rank programming events. In this alternative embodiment, amatch between a qualified keyword of a viewer profile a metadata keywordor a word included in descriptive data of the metadata produces aqualified keyword match score when the metadata includes a goodness offit score for the category specified in the viewer profile for thequalified keyword. A qualified keyword match preferably encompasses bothexact matches between keywords and matches between roots of keywords.The keyword match score assigned to a qualified keyword match ispreferably greater than a greatest possible simple keyword match score,so that any programming event having a qualified keyword match is rankedhigher than any programming event having only a simple keyword and/orcategory match. This reflects a presumption that a programming eventmatching a qualified keyword provided by a viewer is more likely tosatisfy the viewer's preferences than a programming event matching asimple keyword or the viewer's specified categories. Of course,alternatives to the present embodiment may implement different scoringreflecting different presumptions.

The qualified keyword match score is preferably determined using aconstant that is assigned to each qualified keyword match and that isaugmented in each case by quantity that is determined using thepreference score associated with the category of the qualified keywordin the viewer profile of the qualified keyword. In this manner thequalified keyword matches are ranked relative to one another based onthe preferences for their associated categories expressed by the viewer.Alternative manners of ranking qualified keyword matches may also beemployed, for example, using a preference score associated with thequalified keyword in the viewer profile that produces the qualifiedkeyword match, or the length of the programming event, or a categorymatch score determined for the programming event using the categorypreference scores of the viewer profile that produces the qualifiedkeyword match, or the goodness of fit score of the qualified keyword'scategory in the programming event metadata.

A basic process in a client device encompassing the second alternativepreferred embodiment and various implementations thereof is illustratedin FIG. 19. Initially metadata is received (238). The metadata describesprogramming events, and includes goodness of fit scores associated withcategories of a classification hierarchy. The metadata further includesat least one of descriptive data, such as is illustrated in theProgram_Description and Program_Reduced_Description fields of themetadata of FIG. 7, and keyword data, as illustrated in the Keyword_Listfield of FIG. 7. After receiving metadata, the programming events areranked (240) in accordance with viewer preferences expressed in one ormore viewer profiles. The viewer profiles include preference scoresassociated with categories of the classification hierarchy and one ormore keywords. The keywords may be qualified keywords or simplekeywords. The ranking uses the metadata goodness of fit scores and theviewer profile category preference scores to determine category matchesand uses the metadata descriptive data and/or keyword data and theviewer profile keywords and qualified keywords to determine keywordmatches.

In further alternative embodiments, the matching processing in theclient device may process qualified and simple keywords in a unifiedmanner by treating unqualified keywords as qualified keywords that areassociated with a super category of the classification hierarchy thatencompasses all other categories.

It is noted that in embodiments such as the various alternativepreferred embodiments described above, in which ranking is based onscores generated using two or more different types of matches, it ispossible for a viewer profile to generate more than one match score fora programming event. For example, a viewer profile may generate both akeyword match and a category match for the programming event. In suchembodiments, it is preferred to use the highest score for purposes ofranking. Alternatively, in further embodiments a single function ofcategory, keyword and qualified keyword matches may be employed togenerate a single score for each programming event.

In addition, it is preferable in the aforementioned preferredembodiments to apply thresholding processes that exclude keywords orcategories from match processing where preference scores or goodness offit scores are below a threshold value. For example, where the categoryof a qualified keyword has a goodness of fit score below a threshold fora given programming event, the qualified keyword may be excluded fromanalysis of that programming event.

The aforementioned systems and methods may be employed to provide aclient device that generates a preferred programming event list and usesthat list to provide alerts or to record programming events. In oneembodiment of such systems, the timing of the alerts or recording may bedetermined with reference to time maintained by a client local clockusing timing information contained in programming event metadata, suchas a beginning time and duration, to determine the actual start time ofthe programming event. Client local clocks may be synchronized to aglobally available timing reference such as the time signal provided bythe Public Broadcasting System.

However, it may often be the case that timing information contained inprogramming event metadata does not represent the actual local clocktime at which a programming event will begin. This may occur for avariety of reasons. For example, different programming event providerssuch as television broadcasters may not be synchronized to the sameglobal timing reference. Thus, for example, the beginning of the noonhour broadcast on one network may begin earlier or later than that ofanother network by as much as a minute or more, and therefore the clientlocal clock may be synchronized to only one, or possibly to neither ofthe programming event providers. As a result, a recording that iscommenced based on the local clock time may not fully capture thedesired programming event or may capture unwanted matter. Also, inmulti-segmented programs such as news broadcasts, the predicted timesand durations expressed in the metadata for each segment may not beadhered to during the actual broadcast, since the nature of suchprograms can be fluid with some segments running shorter or longer thanpredicted. Similarly, some programming events such as sporting eventsmay exceed their scheduled time, causing subsequent events to bedelayed.

Accordingly, it is desirable to provide timing references in the signalsof the individual programming event providers that may be used by clientdevices to accurately determine the beginning and ending points ofindividual programming events. In accordance with one preferredembodiment, the closed caption data stream is used to convey programmingevent timing information to client devices. The EIA608B standard foranalog closed caption data and the EIA708B standard for digital closedcaption data include protocols for “hidden” data that is not reproducedon the viewer's display and that therefore may be used for signaling.Thus the closed caption data stream from a given programming eventprovider may incorporate timing signals that are used by client devicesto accurately determine the beginning and ending time of eachprogramming event. In accordance with alternative embodiments, timinginformation may be included in the video signal itself. For example, inanalog video signals the timing information may be included in avertical blanking interval. In digital video signals the timinginformation may be provided in a data field of the digital video signal.

In a first preferred embodiment, a closed caption data stream includes aprogramming event identifier that is synchronized with the beginning ofthe corresponding programming event. FIG. 20 shows an example of aclosed caption data stream in accordance with the preferred embodiment.In the closed caption data stream, text corresponding to a programmingevent designated as “PE 1” (programming event 1) precedes textcorresponding to a following programming event designated as “PE 2”(programming event 2). Immediately prior to the text data for PE 2 is anidentifier for programming event 2. The identifier is preferably thesame identifier for programming event 2 that is used in metadata forprogramming event 2 previously supplied to client devices, and may beobtained through interaction with a local or remote metadata generator.However, other types of identifiers may be used so long as they can berecognized by client devices as relating to a particular programmingevent. The timing data is preferably accompanied by a marker thatidentifies it as timing data, and the timing data is preferablyencrypted.

As an alternative to the arrangement of timing data shown in FIG. 20,timing data may be embedded in the closed caption data stream at alocation prior to the beginning of a programming event in order toafford sufficient set-up time for recording in the client device. Forexample, the timing data may be located at a fixed time prior tocommencement of the programming event, for example, five seconds beforethe programming event. Alternatively, the timing data may be located atan arbitrary time prior to the programming event and may includeinformation indicating the amount of time remaining before the beginningof the corresponding programming event.

As an enhancement to the aforementioned preferred embodiments, theclosed caption data may also include timing data that corresponds to theend of a programming event. As with the beginning timing data, the endtiming data may comprise an identifier located at the end of theprogramming event, or at a fixed or specified time prior to the end ofthe programming event. The timing data indicating the end of theprogramming event may be timing data specifically defined as end pointidentifying timing data of the programming event being recorded, or itmay be timing data indicating the beginning of the next programmingevent. As a further enhancement, the closed caption timing data mayinclude timing data indicating beginnings and endings of individualsegments within a programming event. For example, where a programmingevent to be recorded is a television program that includes commercialbreaks, the closed caption timing data may indicate points at whichcommercial breaks begin and end so that a recording device can use thetiming data to exclude the commercial portions from recording, deletethe commercial portions subsequent to recording, or skip the commercialportions during playback.

Thus in accordance with preferred embodiments of the invention, aprocess for producing closed caption data including programming eventtiming data of the types described above or other alternative types maybe implemented in a video production facility to produce closed captiondata including timing data at the time of production of the videoprogram. Generally, script data is received for a video program.Identifiers of individual programming events within the program are thendetermined. This may be done using the script data and other productiondata in a metadata generation process such as the metadata generationprocesses described above. Closed caption data is then produced for theprogram. The closed caption data includes text data corresponding to thescript data, and timing data. The timing data is provided at locationswithin the closed caption data that correspond to the beginnings of eachprogramming event within the program, and the timing data for eachprogramming event includes the identifier of that programming event.Additional closed caption timing data may also be provided at locationscorresponding to the ends of programming events and to the beginningsand endings of segments within programming events. The producer mayfurther provide synchronized transmission of the closed caption data andprogramming events, or may store the programming events and closedcaption data on a machine readable storage medium.

In accordance with alternative embodiments of the invention, a processfor producing a video signal including programming event timing data ofthe types described above or other alternative types may be implementedin a video production facility to produce a video signal includingtiming data at the time of production of the video program. Generally,the beginnings of programming events within the program and identifiersof each programming event are determined. This may be done using scriptdata and other production data in a metadata generation process such asthe metadata generation processes described above. A video signal isthen produced for the program. The video signal includes timing datathat is provided at locations within the video signal at locations thatcorrespond to the beginnings of each programming event within theprogram, and the timing data for each programming event includes theidentifier of that programming event. Additional timing data may also beprovided at locations corresponding to the ends of programming eventsand to the beginnings and endings of segments within programming events.

In a further embodiment, the production of closed caption timing data isimplemented in a manner that is preferred for providing enhancedsynchronization for video programs, and particularly for “live” videoprograms and other programs produced using a teleprompter. In such videoprograms, the exact timing of transitions between programming eventswithin the program can depends on the rate at which narration withineach programming event occurs. For example, the length of segments of anews program depends on the rate at which a news anchor reads the textof each segment. FIG. 21 illustrates basic components of a videoproduction system in accordance with preferred embodiments for enhancingsynchronization with client devices. The video production systemincludes a video source 242 for providing the program video signal 244.The system further includes a closed caption data source 246 forproviding a closed caption data stream 248 including closed caption textdata and timing data such as the timing data described above. The closedcaption data and video signal are provided to a storage device or atransmission medium 250. In addition, the system includes a telepromptersystem 252 that displays text to be read during the production of thevideo program, such as by news anchors or actors. The teleprompter textis generally prepared in advance of the program and in typicalimplementations the teleprompter text and the closed caption text areprepared from the same source and are therefore identical or verysimilar. The teleprompter displays text in a scrolling fashion that isregulated in accordance with the rate at which the text is being read.Thus in typical teleprompter system implementations the scrolling of theteleprompter text is used to trigger corresponding portions of theclosed caption text data, thereby producing a high degree ofsynchronization between the audio portion of the program and thecorresponding closed caption text data. In accordance with preferredembodiments of the invention as illustrated in FIG. 21, the closedcaption data source provides text 254 for display by the telepromptersystem 252, and the teleprompter system 252 provides a trigger signal256 to trigger the transmission of portions of closed caption data thatincludes timing data such as the various types of timing data describedabove. This provides a high degree of synchronization between the timingdata and transitions between programming events.

Thus in accordance with preferred embodiments of the invention, aprocess for generating closed caption data for a video program generallyinvolves producing closed caption data comprising timing data and textdata and producing a video signal for the video program. The locationsof timing data within the closed caption data may correspond tobeginnings or endings of programming events within the video program,and the closed caption data is synchronized to the video signal inaccordance with the display of corresponding data by a telepromptersystem used in producing the video program. The synchronized videosignal and closed caption data may be transmitted to client videoreception devices or stored on a machine readable storage medium.

The closed caption timing data described above may be used in clientvideo devices for synchronizing recording of programming events to thereception of those programming events. Typically, the timing datarepresented in programming event metadata is used for determining apreferred programming event list, while the closed caption data streamis monitored for a period prior to the anticipated commencement of aprogramming event to detect closed caption timing data signifying theactual beginning of the programming event. The closed caption datastream may also be monitored during reception of the programming eventto detect further timing data signifying an end point of the programmingevent or points at which recording should be paused or reinitiated afterpausing. A process for selectively recording programming events asillustrated in FIG. 22 may therefore be implemented in a video recordingdevice. Initially a programming event to be recorded is determined(258). The programming event to be recorded may be determined from arecording schedule based on the current time maintained by the recordingdevice. Timing data associated with the programming event is thenidentified (260) in a closed caption data stream received by therecording device. In some instances it may be necessary for therecording device to tune to the channel of the programming event inadvance of the beginning of the programming event in order to receivethe closed caption data stream of that channel so that the timinginformation indicating the beginning of the programming event may bedetected. The recording device may then control (262) recording of theprogramming event in accordance with the timing data. Such control mayinclude initiating recording, pausing recording, reinitiating recordingafter pausing, or terminating recording.

In alternative embodiments, timing data incorporated directly into thevideo signal as described above may be used in a similar manner in arecording device by detecting the timing data within the video signalrather than within closed caption data.

Where the timing data comprises a simple identifier located at thebeginning of the programming event, delays in commencing recording uponreceipt of the timing data may be resolved through buffering of thevideo stream in the client device. Such delays may be avoided throughthe use of timing data that is located prior to the beginning of theprogramming event by a predetermined or specified distance as describedabove.

Alternative embodiments of the invention may employ different methods ofusing closed caption timing data or timing data provided within thevideo to synchronize recording to programming event transmission. Forexample, a recording device may begin recording the channel of aprogramming event in advance of the beginning of the programming event,and subsequently delete material recorded prior to the beginning of theprogramming event indicated by the corresponding timing data. Materialrecorded after the end of the programming event or during commercialbreaks or other segments indicated by the timing data may be determinedand deleted in a similar fashion.

In still further embodiments, timing data as described above may simplybe recorded in the closed caption data stream accompanying theprogramming event or in the video signal itself, and used later by thedevice to control playback, such as by beginning playback in accordancewith timing data indicating the beginning of the programming event,skipping portions such as commercial breaks indicated by the timingdata, and ending playback in accordance with timing data indicating theend of the programming event.

In still further embodiments, additional information may accompany thetiming information in the closed caption data or video signal.

Although the scoring and scheduling processes described above arepresented in the context of a client device that analyzes metadata forpurposes of identifying upcoming programming events to be recommended orrecorded, alternative embodiments of the invention may implement thescoring and scheduling processes in a server of a programming eventdistribution system that analyzes programming events to determineprogramming events of interest to particular viewers so that thoseprogramming events can be recommended for transmission or automaticallytransmitted. Such a system is illustrated in FIG. 23, in which ametadata distributor 180 supplies metadata 182 to a programming eventprovider 184, which in turn supplies preferred programming events 186 toa client device 188. In embodiments of this system, the client devicemay be a set top box, a computer, or a television. The programming eventprovider may be a broadcast, cable, or satellite television providersystem, or an internet server or video server. The programming eventprovider is typically implemented as a computing device including aprocessor or processors to execute programming instructions and memorycoupled to the processor(s) and containing programming instructions forinstantiating a programming event provider system providing programmingevent scoring and transmission as described further below.

The programming event provider system may perform scoring or schedulingprocesses as described above to assign scores to programming eventsusing programming event metadata and viewer profiles provided by one ormore consumers. For example, as shown in FIG. 24, the programming eventprovider may receive one or more viewer profiles from viewers (190). Theviewer profiles may be provided, for example, by client devices. Asdescribed above, the viewer profiles include preference scoresassociated with categories of a classification hierarchy. Theprogramming event provider also receives metadata for one or moreprogramming events (192). As described above, the metadata includesgoodness of fit scores for categories of the classification hierarchy.Metadata for programming events is processed using the viewer profilesto determine preferred programming events (194). In various embodiments,the metadata may be processed using a single viewer profile to determinepreferred programming events for one viewer or a groups of viewers, orthe metadata may be processed using multiple viewer profiles todetermine preferred programming events for a group of viewers. Preferredprogramming events are then transmitted to the one or more viewers(196). Transmissions may be provided in accordance with a preferredprogramming event schedule as described above. Alternatively, an indexof preferred programming events may be made accessible to viewer toallow viewers to select programming events for transmission.

Further alternative embodiments of the invention may implement aprogramming event scoring process in a server that analyzes programmingevents to determine programming events of particular interest to aviewer and provides alerts regarding the programming events to theviewer through a communication device such as a pager, email, instantmessaging, telephone, or wireless communication device to alert theviewer to the availability of the programming event, and to providerelated information such as the time and channel of the programmingevent and a description of the programming event.

Such a system is illustrated in FIG. 25, in which a metadata distributor200 supplies metadata 202 to a server 204, which determines preferredprogramming events in accordance with a viewer profile and communicatesprogramming alerts 206 to a communication device 208 of the viewer. Thecommunication device may for example be a pager, cell phone, wirelesscommunication device, telephone or computer. The server may performscoring processes as described above to assign scores to programmingevents using programming event metadata and a viewer profile provided bythe viewer. For example, as shown in FIG. 26, the programming eventprovider may receive a viewer profile from a viewer (210). A viewer mayprovide a viewer profile, for example, by transmitting a previouslyestablished viewer profile to the server through the internet, or byaccessing the server through the internet and filling a form to provideappropriate viewer profile information. As described above, the viewerprofile may include preference scores associated with categories of aclassification hierarchy. The viewer profile preferably contains contactinformation, such as an email address or pager number, for indicatingwhere an alert should be sent for that viewer. The programming eventprovider also receives metadata for one or more programming events(212). As described above, the metadata may include goodness of fitscores for categories of the classification hierarchy. Metadata forprogramming events is processed using the viewer profile to determinepreferred programming events (214). An alert is then provided to theviewer's communication device (216). In preferred embodiments the alertis provided to the viewer's communication device using contactinformation such as an email address or pager address that is includedin the viewer profile. The alert may be in the form of a text messagefor viewing, or in the case of wireless communication devices such asdigital cellular telephones, the alert may be provided as acomputer-generated spoken message. The manners of transmitting data froma server to various communication devices as described above is known inthe art. The time at which the alert is provided is preferablydetermined through reference to the time of the preferred programmingevent and information in the viewer profile specifying an amount of timein advance for providing alerts.

Although the processing of the aforementioned embodiment is described asoccurring in a server, alternative embodiments may locate the sameprocessing in a viewer's client device, such that the client devicereceives metadata and processes the metadata to provide programmingalerts to a viewer's communication device. The client device inaccordance with such embodiments will include an appropriate interfacefor providing the programming alerts through a desired communicationsystem.

In further alternative embodiments, systems and processes as discussedabove may be applied to programming events involving other types ofmedia. For example, metadata may be generated for audio programs orsegments of audio programs, and the metadata may be analyzed usingviewer profiles to determine an alert list or programs to be recorded.Analogous processes may be applied to other media such as electronicprint media.

The foregoing description relates to preferred embodiments of theinvention. However, those having ordinary skill in the art willrecognize a variety of alternative organizations and implementationsthat fall within the spirit and scope of the invention as defined by thefollowing claims.

1. A method in a programmable computing device for determining thedesirability of programming events, the method comprising executingprocessing comprising: receiving metadata describing programming events,the metadata that describes a programming event being comprised of atleast one of descriptive data and keyword data; determining a keywordmatch score for each programming event having a keyword match, wherein akeyword match is a match of the at least one of descriptive data andkeyword data of the programming event metadata and a keyword of the atleast one viewer profile, and ranking the programming events inaccordance with the keyword match scores for each programming event. 2.The method claimed in claim 1, wherein said programming event metadatafurther comprises a time and duration of the corresponding programmingevent, and wherein the method further comprises determining aprogramming event recording schedule in accordance with said ranking ofsaid programming events and the times and durations of the programmingevents.
 3. The method claimed in claim 1, wherein said programming eventmetadata further comprises a time of the corresponding programmingevent, and wherein the method further comprises determining aprogramming event alert schedule in accordance with said ranking of theprogramming events and the times of the programming events.
 4. Themethod claimed in claim 3, further comprising displaying a graphicalalert for a programming event in accordance with the alert schedule 5.The method claimed in claim 4, wherein the alert includes at least oneof a title and a description of the programming event.
 6. The methodclaimed in claim 4, wherein the alert includes a keyword that generateda highest score for the programming event in said ranking process. 7.The method claimed in claim 6, wherein the alert further includes ascore associated with the keyword included in the alert.
 8. The methodclaimed in claim 3, wherein the metadata describing programming eventsincludes metadata describing individual segments of television programs,and wherein the programming event for which the alert is displayed is asegment of a television program.
 9. The method claimed in claim 1,wherein the metadata for a programming event further comprises goodnessof fit scores associated with respective subject matter categories,wherein a goodness of fit score represents the degree to which thecorresponding category is descriptive of the subject matter of theprogramming event, wherein the method further comprises determining acategory match score for each programming event as a function of themetadata goodness of fit scores and viewer profile preference scores ofmatched categories of the programming event, wherein a matched categoryis a category for which there is a goodness of fit score in the metadataof the programming event and a preference score in a viewer profile,wherein said ranking is performed in accordance with the keyword matchscores for each programming event and the category match scores for eachprogramming event.
 10. The method claimed in claim 9, whereinprogramming events having keyword matches are ranked higher thanprogramming events not having keyword matches, and programming eventsnot having keyword matches are ranked based upon category matches. 11.The method claimed in claim 9, wherein said programming event metadatafurther comprises a time and duration of the corresponding programmingevent, and wherein the method further comprises determining aprogramming event recording schedule in accordance with said ranking ofsaid programming events and the times and durations of the programmingevents.
 12. The method claimed in claim 9, wherein said programmingevent metadata further comprises a time of the corresponding programmingevent, and wherein the method further comprises determining aprogramming event alert schedule in accordance with said ranking of theprogramming events and the times of the programming events.
 13. Themethod claimed in claim 12, further comprising displaying a graphicalalert for a programming event in accordance with the alert schedule 14.The method claimed in claim 13, wherein the alert includes at least oneof a title and a description of the programming event.
 15. The methodclaimed in claim 13, wherein the alert includes at least one of acategory and a keyword that generated a highest score for theprogramming event in said ranking process.
 16. The method claimed inclaim 15, wherein the alert further includes a score associated witheach category or keyword included in the alert.
 17. The method claimedin claim 13, wherein said metadata describing programming eventsincludes metadata describing individual segments of television programs,and wherein the programming event for which the alert is displayed is asegment of a television program.
 18. The method claimed in claim 1,wherein the metadata for a programming event further comprises goodnessof fit scores associated with respective subject matter categories,wherein a goodness of fit score represents the degree to which thecorresponding category is descriptive of the subject matter of theprogramming event, wherein the method further comprises determining aqualified keyword match score for each programming event having aqualified keyword match, wherein a qualified keyword is a keyword thathas been associated with a particular subject matter category in theviewer profile, and wherein a qualified keyword match is a match betweena qualified keyword of the viewer profile and the at least one ofdescriptive data and keyword data of the metadata of a programming eventthat has a goodness of fit score for the category associated with thequalified keyword in the viewer profile, and wherein said ranking isperformed in accordance with the qualified keyword match scores for eachprogramming event, the keyword match scores for each programming eventand the category match scores for each programming event.
 19. The methodclaimed in claim 18, wherein programming events having keyword matchesare ranked higher than programming events not having keyword matches,and programming events not having keyword matches are ranked based uponcategory matches.
 20. The method claimed in claim 18, wherein saidprogramming event metadata further comprises a time and duration of thecorresponding programming event, and wherein the method furthercomprises determining a programming event recording schedule inaccordance with said ranking of said programming events and the timesand durations of the programming events.
 21. The method claimed in claim18, wherein said programming event metadata further comprises a time ofthe corresponding programming event, and wherein the method furthercomprises determining a programming event alert schedule in accordancewith said ranking of the programming events and the times of theprogramming events.
 22. The method claimed in claim 18, furthercomprising displaying a graphical alert for a programming event inaccordance with the alert schedule
 23. The method claimed in claim 22,wherein the alert includes at least one of a title and a description ofthe programming event.
 24. The method claimed in claim 22, wherein thealert includes at least one of a category, a keyword and a qualifiedkeyword that generated a highest score for the programming event in saidranking process.
 25. The method claimed in claim 24, wherein the alertfurther includes a score associated with each category, keyword orqualified keyword included in the alert.
 26. The method claimed in claim22, wherein said metadata describing programming events includesmetadata describing individual segments of television programs, andwherein the programming event for which the alert is displayed is asegment of a television program.